From e920b3e514e717fc05ed524267d3b53e272fec51 Mon Sep 17 00:00:00 2001 From: Naeem Model Date: Mon, 6 Jan 2025 23:55:43 +0000 Subject: Update web app entry point - Rename 'app' -> 'web' - Return shiny app object in entry point function --- .../templates/content/estimation/about-estimators/seq_bayes.html | 9 --------- 1 file changed, 9 deletions(-) delete mode 100644 inst/app/templates/content/estimation/about-estimators/seq_bayes.html (limited to 'inst/app/templates/content/estimation/about-estimators/seq_bayes.html') diff --git a/inst/app/templates/content/estimation/about-estimators/seq_bayes.html b/inst/app/templates/content/estimation/about-estimators/seq_bayes.html deleted file mode 100644 index 8f66ab4..0000000 --- a/inst/app/templates/content/estimation/about-estimators/seq_bayes.html +++ /dev/null @@ -1,9 +0,0 @@ -The sequential Bayes (seqB) estimator uses a Bayesian approach to estimate R0 which updates the reproductive number estimate as data accumulates over time. -This approach is based on the SIR model, and assumes that the mean of the serial distribution (ie. the serial interval (SI)) is known. -It is assumed that infectious counts are observed at periodic times (ie. daily, weekly). -This method cannot handle datasets where there are no new infections observed in a time interval, thus, to remedy this, -some manipulation may be necessary to make the times at which infectious counts are observed sufficiently course (ie. weeks instead of days). -Further, this method is also inappropriate in situations where long intervals between cases are observed in the initial stages of the epidemic. -Finally, the R0 approximation behaves similarly to a branching process, which means that throughout, the population size “available” to be infected remains constant. -We note that this assumption does not hold for the SIR/SEIR/SEAIR compartmental models. -As such, seqB estimates should only really be considered early on in an epidemic, ie. before the inflection point of an epidemic, if the dataset being used follows these models. -- cgit v1.2.3